New testing approaches for mean–variance predictability

Gabriele Fiorentini and Enrique Sentana

Journal of Econometrics, 2021, vol. 222, issue 1, 516-538

Abstract: We propose parametric tests for serial correlation in levels and squares that exploit the non-normality of financial returns. Our tests are robust to distributional misspecification. Furthermore, our mean predictability tests can be robustified against time-varying volatility. Local power analyses confirm their gains over existing methods, while Monte Carlo exercises assess their finite sample reliability. We apply our tests to quarterly returns on the five Fama–French factors for international stocks, whose distributions are mostly symmetric but fat-tailed. Our results highlight noticeable differences across regions and factors and confirm the numerical sensitivity of the usual tests to influential observations.

Keywords: Financial forecasting; Moment tests; Misspecification; Robustness; Volatility (search for similar items in EconPapers)
JEL-codes: C12 C22 G17 (search for similar items in EconPapers)
Date: 2021
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Related works:
Working Paper: New testing approaches for mean-variance predictability (2019)
Working Paper: New testing approaches for mean-variance predictability (2019)
Working Paper: New testing approaches for mean-variance predictability (2019)
Working Paper: New Testing Approaches for Mean-Variance Predictability (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:222:y:2021:i:1:p:516-538

DOI: 10.1016/j.jeconom.2020.07.014

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